1. Field of the Invention
The invention relates to a method and system for integrated assessment, coding and scoring of overall health and, more specifically, at times when communication and decision-making are particularly crucial such as in the assessment of perioperative risk.
2. Description of the Related Art
The complex physiological demands wrought by anesthesia and surgery may have a significant impact on a patient's pre-existing medical conditions, necessitating a vital role for anesthesiologists as perioperative as well as intraoperative physicians. While the medical imperative for this role is substantial, the health system framework required for its optimal execution is comparatively weak. The financially driven migration of inpatient surgeries to day-of-surgery admissions and outpatient procedures has virtually eliminated face-to-face conversations among clinicians at the patient's bedside on the evening prior to surgery. Moreover, the anesthesiologist caring for the patient no longer is assured access to the patient (or detailed information about the patient) prior to the day of surgery. In some centers, this lack of communication has led to establishment of pre-admission centers that integrate assessments by the anesthesiologist, surgeon, long-term care provider, and consultant. However, in many cases, the multifaceted process of preoperative assessment and preparation has become the primary responsibility of either a primary care physician without first-hand knowledge of the operative plan or of an anesthesiologist or surgeon with limited knowledge of the patient's long-term care.
Furthermore, for those institutions where preanesthesia evaluation clinics exist, they are frequently staffed by non-anesthesiologists or an anesthesiologist who will not be in charge of the patient's intraoperative care. In the absence of a well-developed information network, this opens the substantial risk of important clinical data being lost or misinterpreted within a series of information transfers. In addition, the presence of multiple care providers (for example, surgeon, anesthesiologist, internist, consultants) in the face of imprecise role definitions all too frequently results in errors of omission due to unreliable communication. The present invention was prompted to fill the void (that is, loss of the “bedside” encounter) imposed by day of surgery admissions with an even more effective, universally applicable means of assessment and communication.
It has been suggested that perioperative risk be interpreted as being influenced by two major components: the patient's physical status and the planned surgical invasiveness. Lema M J, Using the ASA Physical Status classification may be a risky business, ASA Newsletter 2002; 66(9).
In the early 1940s, the American Society of Anesthesiologists (ASA) had the wisdom to design a simple 1 to 5 score that would enable anesthesiologists to communicate the severity of a patient's illness among themselves and with physicians in other specialties. This resulted in what is currently known as the ASA Physical Status (PS) Classification System. One of the stated purposes of the endeavor was to develop a means by which to develop statistical data about anesthetic outcomes by controlling for differences in a patient's underlying medical conditions. Saklad M., Grading of patients for surgical procedures, Anesthesiology 1941 May:281-284.
Sixty years later—with only minor revisions despite major advances in anesthesia, surgical and medical care—the ASA PS system remains the most widely used patient classification scheme in anesthesiology.
While its simplicity is one of its strengths, it is also one of its limitations. The ASA PS score does not distinguish between disorders of different systems or the nature of different disorders within the same system. Rather, it provides a single number to represent the systemic severity of the patient's overall medical condition. Hence, a given score does not guide preparation for a patient with asthma vs. renal disease vs. cardiac disease vs. metastatic malignancy. Moreover, it does not delineate or cumulate risk based upon multiple disorders. This has prompted the inventor to hypothesize that, with respect to the ASA score, the whole is less than the sum of its parts. In a recent assessment of 220 patients that underwent preoperative assessment under my supervision at a tertiary care medical center and received an ASA physical status score of 3 (significant systemic condition), or 4 (life-threatening systemic condition):                the distribution among bodily systems was not uniform, with 55.7% having what the inventive system described herein would rate as a ≧3 (on a 1-5 scale) cardiac disorder;        30.4% of patients had two systems affected by significant dysfunction, 14.1% had three systems, and 2.1% had four systems.        
Other methods of classifying patients with respect to physical condition have been developed, but these have tended to focus on discrete subpopulations. Several authorities have developed systems for stratifying perioperative cardiovascular morbidity and mortality. Palda V A. Detsky A S, Perioperative assessment and management of risk from coronary artery disease, [Review, Tutorial] Annals of Internal Medicine, 127(4):313-28, 1997 Aug. 15., Detsky A S, Abrams H B, Forbath N, Scott J G, Hilliard J R, Cardiac assessment for patients undergoing noncardiac surgery. A multifactorial clinical risk index, Arch Intern Med 1986; 146(11):2131-4. These systems typically emphasize cardiovascular evaluation to the exclusion of other disease processes. In the critical care literature, the development of risk stratification indices also has been popular. However, these systems, which include the Charlson Comorbidity index, Mortality Probability Model and APACHE score, focus on disorders with high morbidity and mortality that do not necessarily pose as high a risk as other conditions in the acute perioperative period. For example, the Charlson index provides scores of 1 and 6 for prior myocardial infarction (a finding that significantly increases the risk of an adverse cardiac event in the perioperative) and metastatic malignancy, respectively Scales D C, Laupacis A, Pronovost P J, A systematic review of the Charlson comorbidity index using Canadian administrative databases: a perspective on risk adjustment in critical care research, Journal of Critical Care 2005; 20(1):12-19. (As will be shown later, the indices have little in common with the major components of the present invention.
Scoring systems have also been described for specific disorders. For example, the Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure classifies three stages of hypertension: prehypertension (systolic 120-139 mmHg, diastolic 80-89 mmHg), Stage 1 (systolic 140-159 mmHg, diastolic 90-99 mmHg), and Stage 2 (systolic>160 mmHg, diastolic>100 mmHg) in light of the direct relationship between elevated blood pressure and risk of morbidity. Similarly, the New York Heart Association defines four classes of heart failure based on degree of physical limitation—from no limitation (Class I) to incapacitation (Class IV). Examples exist for noncardiac disorders as well. For example, the Child-Pugh score provides a means to grade the severity of liver disease based on clinical symptoms and laboratory data; and five stages of renal dysfunction have been delineated by the National Kidney Foundation based on glomerular filtration rate. Other rating systems integrate signs and symptoms to generate qualitative gradations by which the severity of the condition and the adequacy of therapeutic management are judged. For example, diabetes control is evaluated based on glycosylated hemoglobin, insulin requirements, blood glucose readings before and after meals, tendency for harmful extremes, and end-organ injury. Scoring of asthma severity is based on frequency and severity of symptoms and inhaler use.
Relative to these systems, the assignment of ASA PS is significantly more subjective. For this reason, it is not surprising that numerous studies have demonstrated significant inter-rater variability in scoring, leading some to doubt the ASA PS's clinical utility particularly when used as a communication tool among practitioners. Aronson W L, McAuliffe M S, Miller K, Variability in the American Society of Anesthesiologists Physical Status Classification Scale, AANA J 2003; 71 (4):265-274; Mak P H, Campbell R C, Irwin M G, American Society of Anesthesiologists. The ASA Physical Status Classification: inter-observer consistency American Society of Anesthesiologists. Anaesth Intensive Care 2002; 30(5):633-40; Owens W D, Felts J A, Spitznagel E L, Jr., ASA physical status classifications: a study of consistency of ratings, Anesthesiology 1978; 49(4):239-43; Ranta S, Hynynen M, Tammisto T, A survey of the ASA physical status classification: significant variation in allocation among Finnish anaesthesiologists, Acta Anaesthesiol Scand 1997; 41(5):629-32. Nonetheless, there are several reasons why, despite its shortcomings, the ASA PS system has endured. First, it can be determined based on information obtained from a history and physical examination without the need for additional data. Second, its five-point scoring system is intuitive and easy to remember. In addition, unlike other illness severity scoring tools, the ASA PS was designed to be applied to patients of all ages, medical conditions, and degrees of health.
The ASA PS was intended to reflect the condition of an individual irrespective of the planned surgical procedure. However, without knowing the degree of surgical invasiveness planned, the ability to assess perioperative risk is limited. Hence, the need for a system by which to classify surgical severity was recognized; and several surgical risk scoring systems have been proposed. Brooks M J, Sutton R, Sarin S, Comparison of Surgical Risk Score, POSSUM and p-POSSUM in higher-risk surgical patients, Br J Surg 2005; 92(10):1288-92; Pasternak L R, Preoperative evaluation, testing, and planning, Anesthesiol Clin North America 2004; 22(1):xiii-xiv; Pasternak L R, Preanesthesia evaluation of the surgical patient, Clinical Anesthesia Updates 1995; 6(2):1-12; Eagle K A, Berger P B, Calkins H, et al., ACC/AHA guideline update on perioperative cardiovascular evaluation for noncardiac surgery: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Committee to Update the 1996 Guidelines on Perioperative Cardiovascular Evaluation for Noncardiac Surgery). 2002.}. The American College of Cardiology/American Heart Association (ACC/AHA) has divided surgeries into low-, intermediate- and high-risk in its guidelines for preoperative evaluation of patients with coronary artery disease. Eagle K A, Berger P B, Calkins H, et al., ACC/AHA guideline update on perioperative cardiovascular evaluation for noncardiac surgery: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Committee to Update the 1996 Guidelines on Perioperative Cardiovascular Evaluation for Noncardiac Surgery), 2002. Pasternak and colleagues proposed the Johns Hopkins Risk Classification System. Pasternak L R, Preoperative evaluation, testing, and planning, Anesthesiol Clin North America 2004; 22(1):xiii-xiv; Pasternak L R, Preanesthesia evaluation of the surgical patient, Clinical Anesthesia Updates 1995; 6(2):1-12. The John Hopkins Risk Classification System employs a five-level classification based on location and extent of surgery, anticipated blood loss and fluid shift, postoperative anatomic and physiological alterations and the need for postoperative intensive care monitoring. Of note, the 3-tiered ACC/AHA and 5-tiered Pasternak rankings are not interchangeable.
The importance of having a means by which to assess surgical risk as well as preoperative patient evaluation is now well appreciated. In a retrospective study in Great Britain, Fowkes et al. found surgical condition to be the most often cited cause of perioperative death, followed by the severity of the patient's underlying medical condition. (“Anesthesia” was the third most common factor to be implicated). Fowkes F G, Lunn J N, Farrow S C, Robertson I B, Samuel P, Epidemiology in anaesthesia. III: Mortality risk in patients with coexisting physical disease, Br J Anaesth 1982; 54(8):819-825. More recently, the ASA Task Force on Preanesthesia Evaluation made this point clear when advising evaluation by an anesthesiologist prior to the day of surgery not only for ASA 3 or 4 patients but also for relatively healthier ASA 1 or 2 patients undergoing highly invasive, high-risk surgical procedures. American Society of Anesthesiologists Task Force on Preanesthesia Evaluation, Practice advisory for preanesthesia evaluation: a report by the American Society of Anesthesiologists Task Force on Preanesthesia Evaluation, Anesthesiology 2002; 96(2):485-96. Data obtained under my direction at a tertiary care center documented the effects of the ASA PS score and surgical risk/invasiveness on hospital length of stay (FIG. 1).
The relative weighting of variables and the specific formula to predict outcomes can be generated by multivariate logistic regression and other forms of analysis as well as empirical observation. For example, based on the derivation data set of the aforementioned study, the weighted influence of the ASA physical status score and the surgical invasiveness score is shown by the following regression equation generated from the data:Hospital Charges ($)=e[(7.6+0.35(ASA)+0.56(SOCU)−0.55(ASA)(SOCU)]
While, to a certain extent, the combination of ASA PS and degree of surgical invasiveness would suggest the degree of anesthetic risk, there are other factors that impact on anesthetic complexity and perioperative morbidity and mortality. If identified prior to the day of surgery, they likely would be amenable to risk management interventions. The literature is replete with recommendations as to how to characterize, plan for and manage what may be termed “non-ASA PS score, non-surgical invasiveness” factors that affect anesthetic complexity and potentially impact of patient morbidity. However, to the best of my knowledge, until the development of the present invention a system for incorporating these factors in a communicable score was lacking—hence, vital information may not be readily transmitted to the operating room schedulers and intraoperative caregivers and to databases for quality assurance, outcome, financial, resource allocation, and investigative analysis.
Complications of airway management are the most common cause of anesthetic-related catastrophes. Lee L A, Domino K B, The Closed Claims Project. Has it influenced anesthetic practice and outcome? Anesthesiol Clin North America 2002; 20(3):485-501; Cheney F W, The American Society of Anesthesiologists Closed Claims Project: what have we learned, how has it affected practice, and how will it affect practice in the future?, Anesthesiology 1999; 91 (2):552-6; Caplan R A, Posner K L, Ward R J, Cheney F W, Adverse respiratory events in anesthesia: a closed claims analysis, Anesthesiology 1990; 72(5):828-33. For this reason, identification of the potentially difficult airway has been an ongoing clinical endeavor. The Mallampati score of oropharyngeal view has provided some uniformity to prediction of endotracheal intubation difficulty, but is woefully incomplete. Mallampati S R, Clinical sign to predict difficult tracheal intubation (hyothesis), Can Anaesth Soc J. 1983; 30(3 Pt 1):316-317; Mallampati S R, Gatt S P, Gugino L D, et al., A clinical sign to predict difficult tracheal intubation: a prospective study, Can Anaesth Soc J. 1985; 32(4):429-434; Needham D M. Bellhouse C P, Dore C, Predicting difficult intubation, Br J Anaesth 1989; 62(4)469; Combes X, Le Roux B, Suen P, et al., Unanticipated difficult airway in anesthetized patients: prospective validation of a management algorithm, Anesthesiology 2004; 100(5):1146-50; el-Ganzouri A R, McCarthy R J, Tuman K J, Tanck E N, Ivankovich A D, Preoperative airway assessment: predictive value of a multivariate risk index, Anesth Analg, 1996; 82(6):1197-1204; Ovassapian A, Glassenberg R, Randel G I, Klock A, Mesnick P S, Klafta J M, The unexpected difficult airway and lingual tonsil hyperplasia: a case series and a review of the literature, Anesthesiology 2002; 97(1):124-32; Yamamoto K, Tsubokawa T, Shibata K, Ohmura S, Nitta S, Kobayashi T, Predicting difficult intubation with indirect laryngoscopy, Anesthesiology 1997; 86(2):316-321. Furthermore, it does not address other aspects of airway management, most notably potential difficulties associated with ventilation (e.g., via a face mask) and risk of aspiration or precipitous desaturation.
In addition to the airway, issues potentially critical to anesthesia management that should be communicated include conditions such as prior halothane hepatitis or porphyria (a disorder of blood cell enzymes); communication problems; emergency surgery; presence of an AICD (automatic intra-cardiac defibrillator); latex allergy; risk of malignant hyperthermia; morbid obesity; pregnancy; and potential for signs and symptoms of acute withdrawal. Of these, the only one that is communicated as part of the ASA score is emergency surgery, which is designated with an “E” after the numeric score to indicate that there may not be time to optimize the patient's condition preoperatively (a factor that results in a higher level of reimbursement).
It should be noted that, with current practices at a major medical center (without the information provided by the present invention), anesthesiologists reported that they either overestimated or underestimated subsequent case complexity based upon the information available on the operating room schedule in approximately 25% of cases (data obtained by my research team presented at the American Society of Anesthesiologists annual meeting in October 2006 after initial filing of this disclosure).
The need for the present invention and its potential in the perioperative period as well as for consistency, integration, communication, quality and efficiency of overall medical care is evident by the multiple urgings for change summarized in Table 1.
TABLE 1Recent Statements That Suggest The Need for a Program Such As That Described HereinBramhall J. The role of nurses in preoperative assessment. Nursing Times 98(40): 34-5, 2002 Oct 1-8.When patients elect to have surgery, it is vital that they are assessed systematically in the preoperative period.Maccioli GA: Of digital cameras and ATMs. ASCCA Interchange Newsletter 13(3): 2, 2001How is it that medicine, a profession so critically dependent on information, is so utterly Balkanized when it comesto data?Brown MG: Grant will allow doctors to share patient information. Connecticut Post Online“Our current health care system still relies too much on pen-and-paper record-keeping prescribing. It is a systemthat vastly increases the risk of preventable errors that jeopardize our health, lessen the quality of the care wereceive and increase cost,” Gov. M. Jodi Rell said.“The burden will no longer be on the patient to communicate everything that is relevant about their medicalcondition.Horwitz LI, Krumholz HM, Green ML, Huot SJ. Transfers of patient care between house staff on internalmedicine wards. A national survey. Arch Intern Med 2006; 166: 1173-1177Transfers of care are events that are particularly susceptible to commumcation failure, as important informationmay be “lost in transition” between physicians. This is a critical issue for patient safety because communicationfailure is one of the most common root causes of medical error.The Joint Commission on Accreditation of Healthcare Organizations has made “a standardized approach to ‘handoff’ communications” one of its new National Patient Safety Goals for 2006.MSNBC: Hospitals move toward ‘paperless’ age. More health-care providers switch to electronic records.http://www.msnbc.msn.com/id/5592501/According to a recent analysis by the Institute of Medicine, the routine use of electronic records could helpreduce the tens of thousands of deaths and injuries caused by medical mistakes every year.“As patients begin to recognize that hospitals are largely in the dark ages, they will begin to demand that they getthe best care possible, which is in part dependent on hospitals using electronic records,” she said.Tremper KK. Anesthesia information systems: developing the physiologic phenotype database. AnesthAnalg 101(3): 620-621, 2005As the vendors of anesthesia information systems accelerate their implementation in hospitals throughout thecountry, it begs the question: is it time for our specialty to develop a standardized preoperative assessment,intraoperative record, and postoperative visit? If we hope to pool our data on a large scale, it is important that weare collecting the same data elements.Charlson ME. Ales KL. Simon R. MacKenzie CR. Why predictive indexes perform less well in validationstudies. Is it magic or methods? Archives of Internal Medicine 147(12): 2155-61, 1987Important discrepancies in performance of prognostic indexes may arise from differences in surveillance strategiesand definitions of outcome.Jollis JG. Ancukiewicz M. DeLong ER. Pryor DB. Muhlbaier LH. Mark DB. Discordance ofdatabases designed for claims payment versus clinical information systems. Implications for outcomesresearch. Annals of Internal Medicine 119(8): 844-850, 1993Claims data failed to identify more than one half of the patients with prognostically important conditions,including mitral insufficiency, congestive heart failure, peripheral vascular disease, old myocardial infarction,hyperlipidemia, cerebrovascular disease, tobacco use, angina, and unstable angina . . .Chin T: Avoiding EMR meltdown: How to get your money's worth.There are no empirical data or surveys measuring how many de-installs occur annually, but people in the industryestimate that 20% to 33% of EMRs fail within a year of their implementation because physicians are unhappy withthe systems.Fink AS. Campbell DA Jr. Mentzer RM Jr. Henderson WG. Daley J. Bannister J. Hur K. Khuri SF. TheNational Surgical Quality Improvement Program in non-veterans administration hospitals: initialdemonstration of feasibility. Annals of Surgery 236(3): 344-353; discussion 353-354, 2002. . . one of the hurdles we faced in this effort was that even in these three different non-VA centers, we encounteredvery disparate IT systems. Ultimately we will need to develop some kind of mechanism to either circumvent thesedifferences or to create some kind of common IT electronics interface that will facilitate data transmission.Ledger M: Prescription: Better information technology for better health. Penn Medicine 2005, fall, 7-1222 kinds of mistakes which they divided into two groups: information errors generated by fragmentation of dataand failure to integrate the hospital's several computer and information systems; and flaws in the interface betweenhumans and machinesAtherly A. Fink AS. Campbell DC. Mentzer RM Jr. Henderson W. Khuri S. Culler SD. Evaluatingalternative risk-adjustment strategies for surgery. [evaluation studies] American Journal of Surgery188(5): 566-570, 2004 November“different risk-adjustment methodologies afford divergent estimates of mortality risk.”
The problem (which is not limited to the perioperative period) is that the disparate nature of terminology, classification, coding and scoring has been allowed to metastasize, with disparate systems for clinical evaluation, special testing, decision making, communication, resource allocation, quality assurance and research applications. To date, problems in these areas have been addressed with band aids or by trying to adapt programs designed to solve a different problem.
This invention cures these problems treats the underlying “illness” by introducing a new mechanism for data entry, coding and scoring and a mechanism to enable universality among clinical, communicative, administrative and investigative components. The seamless integration of data is enabled with little or no added burden to the clinician in that main impact of the invention is on the information after it has been accrued by the patient's healthcare providers.
Limitations of Other Coding Systems:
The most widely used means for coding medical conditions is the 9th revision of the International Classification of Diseases (ICD, with latest version at time of this submission being ICD-9) system, as detailed in ICD-9-CM for Physicians. (Ingenix, Inc. 2006) (for codes valid Oct. 1, 2005 through Sep. 30, 2006). As noted in that text, “coding today is used to describe the medical necessity of a procedure which then facilitates payment of health services, to evaluate utilization patterns and to study the appropriateness of health care costs.” As noted on p1 of that text, ICD-9 coding is a complex process: “A joint effort between the healthcare provider and the coder is essential to achieve complete and accurate documentation, code assignment and reporting of diagnoses and procedures . . . The entire record should be reviewed to determine the specific reason for the encounter and the conditions treated.”
The following “10 STEPS TO CORRECT CODING” cited by Ingenix's 2006 version of ICD-9-CM for Physicians illustrates the complexity of the ICD system, which is far greater than that of the inventive system. That text states:                Step 1: Identify the reason for the visit (e.g., sign, symptoms, diagnosis, condition to be coded).        Step 2: Always consult the Alphabetic Index, Volume 2, before turning to the Tabular List.        The most critical rule is to begin a code search in the index. Never turn first to the Tabular List (Volume 1), as this will lead to coding errors and less specificity in code assignments. To prevent coding errors, use both the Alphabetic Index and the Tabular List when locating and assigned a score.        Step 3: Locate the main entry term.        Step 4: Read and interpret any notes listed with the main term.        Step 5: Review entries for modifiers        Step 6: Interpret abbreviations, cross-references, symbols and brackets. Cross references used are ‘see,’ ‘see category’ or ‘see also.’ The abbreviation NEC may follow main terms or subterms. NEC (not elsewhere classified) indicates that there is no specific code for the condition even the medical documentation may be very specific. The ✓ box indicates the code requires an additional digit. If the appropriate digits are not found in the index, in a box beneath the main term, you MUST refer to the Tabular list. Italic brackets [ ] are used to enclose a second code number that must be used with the code immediately preceding it and in that sequence.        Step 7: Choose a tentative code and locate it in the Tabular List. Be guided by any inclusion or exclusions terms, notes or other instructions such as ‘code first’ and ‘use additional code,’ that would direct the use of a different or additional code from that selected in the index for a particular diagnosis, condition, or disease.        Step 8: Determine whether the code is at the highest level of specificity. Assign three-digit codes (category codes) if there are no four-digit codes within the code category. Assign four-digit codes (subcategory codes) if there are no five-digit codes for that category. Assign five-digit codes (fifth-digit subclassification codes) for those categories where they are available.        Step 9: Consult the color coding and reimbursement prompts, including the age, sex and Medicare as secondary payer edits. Consult the official ICD-9-CM guidelines for coding and reporting, and refer to the AHA's (American Hospital Association) Coding Clinic for ICD-9-CM for coding guidelines governing the use of specific codes.        Step 10: Assign the code.”        
For many conditions, one needs to refer to a special section titled “Signs, Symptoms and Ill-defined Conditions” of the ICD-9 code to locate signs and symptoms. As stated on page 13 of the Ingenix text: “In addition to the etiology/manifestation convention that requires two codes to fully describe a single condition that affects multiple body systems, there are other single conditions that also require more than one code.”
The widely used CPT (Current Procedural Terminology) code provides a 5-digit code for procedures. These are grouped as “Evaluation and Management, Anesthesiology, Surgery, Radiology, Pathology and Laboratory, Medicine. CPT codes, an established means for designating specific procedures, also have significant shortcomings. As is the case for ICD codes, the CPT coding system lacks the score-based coding that typifies the inventive system. It focuses on procedures rather than diagnoses; and, for many of its codes, CPT coding ignores severity of the precipitating patient illness, the potential multi-system effects of surgery (which, as shown in FIG. 11, may be greater on a system other than that with the underlying surgical pathology—e.g., RESP after an large abdominal incision) and the nature and severity of comorbidities (problems not directly related to the planned procedure but which may impact significantly on the patient's ability to withstand the demands of a procedure such as invasive surgery or the need for/effectiveness of additional diagnosis and therapy.
The lack of a uniform language and code is evident at a major institution about which the author is very familiar. The operating room scheduling system captures the CPT code and anesthesiologists bill according to Relative Value Units, which are based upon CPT codes; but many surgical offices use the ICD-9 disease code, the NSQIP quality assurance program uses specified text entries (or their equivalent), government-mandated Surgical Care Improvement Program (SCIP) measures rely upon ICD-9 codes, and hospital billing has relied upon ICD-9 procedure codes (and a system for crosswalk to establish compatible codes). Each coding system has its coding specialists.
With the foregoing in mind, an improved method and system for perioperative evaluation and communication is required that overcomes the limitations of the prior art, including:                lack of a coding and scoring system that provides consistent, suitably detailed, integrated and readily communicable information about multiple aspects of a patient's medical condition, upcoming challenges (e.g., surgery) and related factors; and        lack of a uniform language, coding system and scoring system for data storage, multiple displays and reports, importing (from other sources), exporting (to multiple diagnostic and treatment algorithms), administrative purposes (quality assurance, resource allocation, and billing) and specific evidence-based research applications.        
The present invention provides such a system and method for assessment, quantification and communication and then details a preferred embodiment and adaptations thereof. While the embodiments detailed herein focus primarily on integrated preoperative assessment, it is within the spirit and scope of this invention to focus on and adapt individual components for assessment in other contexts such as longterm care and management in other acute (e.g., emergency, battlefield, or intensive care) settings as well as for triaging and transferring care among healthcare providers in those contexts. Likewise, a patient may followed at standard intervals during long-term care, with additional assessments as deemed indicated, and with more frequent serial assessments during acute challenges or initiations of new therapies. As detailed later in this disclosure, score-driven communication not only would be of great value for perioperative healthcare providers but at virtually every exchange of information among healthcare providers and between healthcare providers and their patients.